SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1176–1200 of 2226 papers

TitleStatusHype
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference—0
Representation Learning via Variational Bayesian Networks—0
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference—0
RL with KL penalties is better viewed as Bayesian inference—0
Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data—0
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance—0
Robust Bayesian Inference for Berkson and Classical Measurement Error Models—0
Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizers—0
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations—0
Bayesian data-driven discovery of partial differential equations with variable coefficients—0
Robust Energy Storage Scheduling for Imbalance Reduction of Strategically Formed Energy Balancing Groups—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
Robust Gaussian Process Regression with Huber Likelihood—0
Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks—0
Roll-back Hamiltonian Monte Carlo—0
Safe-Bayesian Generalized Linear Regression—0
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis—0
Salient Structure Detection by Context-Guided Visual Search—0
Sampling-based Bayesian Inference with gradient uncertainty—0
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability—0
Sampling Bias Correction for Supervised Machine Learning: A Bayesian Inference Approach with Practical Applications—0
Sampling constrained probability distributions using Spherical Augmentation—0
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset—0
Scalable Bayesian inference for the generalized linear mixed model—0
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks—0
Show:102550
← PrevPage 48 of 90Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified